To schedule large hourly workforces (for example call center agents), most companies utilize Workforce Management (WFM) software-based products that provide forecasting and scheduling capability. The forecasting capabilities typically utilize analytics against historical patterns of demand to predict future demand. An example of a typical WFM system architecture is shown in FIG. 1.
However, WFM systems have a limited ability to deal with situations where the actual demand or supply of agents differs from what has been forecast. For example, if the WFM system forecasts a demand of 200 agents for a given day, and schedules 200 agents accordingly, but the actual demand is 225 agents and only 175 show up to work, the system can do little to enable the company to adjust for the unexpected gap of 50 for that day, beyond offer reporting tools to track staffing level gaps.
Additionally, the processes used to change schedules by entities using traditional WFM systems are generally inefficient and can lead to sub-optimal results. For example, when an agent wants to have his or her schedule changed, he or she will generally be required to contact an administrator (or other individual with authority to make the change) and make a request. The administrator will then consider the agent's schedule and other factors that may be relevant in a given situation and decide whether to approve or deny the change. At best, this type of process will result in additional work for the administrator and wasted time and frustration for anyone waiting to learn if the request is approved or denied. Additionally, it will often result in a sub-optimal scheduling decision being made, since the administrator may not have all relevant data easily available when determining whether to approve the request and, even if all relevant data is easily available, may not have the time to do a complete analysis.
Accordingly, there is a need in the art for improved workforce management technology to deal with intraday staffing gaps and employee initiated change requests.